Recent works in the domain of audiovisual speaker localization showed promising results utilizing different data fusion strategies. For example, [1]}, [2]} introduce a variational Bayesian approximation to optimally merge acoustic and visual data for combined localization and tracking. A related approach introduced in [3]} uses an EM algorithm for weighted clustering in the audiovisual observation space. Other probabilistic techniques for audiovisual speaker tracking based on particle filters were proposed in [4]}, [5]}. Additionally, the work in [6]} combined audiovisual speaker localization with speech separation on a robotic platform in a real-time processing system. A similarly designed audiovisual fusion system for smart rooms [7]} allows for joint localization and identification of persons present in a room.
<FIGURE>